​​Is Your Performance Marketing Team Held Back by a Lack of Data Engineering?

Performance marketing is in the midst of a major transformation. Privacy-focused changes like Apple’s ATT framework and the decline of third-party cookies, have caused a fundamental shift from deterministic to probabilistic attribution. Instead of relying on precise identifiers like IDFA to track users across their buying journey, marketers must leverage probabilistic models and sophisticated data analysis to understand customer behavior and measure campaign performance. 

This new reality, coupled with the increasing volume and complexity of marketing data, has made robust data engineering more critical than ever. Key Performance Indicators (KPIs) like Revenue Per User (RPU), CPMs (Cost Per Thousand), and Click-Through Rates (CTRs) are still critical for understanding campaign performance, but accessing and analyzing the underlying data to calculate these metrics has become more challenging.

The Growing Gap Between Data and Action

Today’s performance marketers face a widening gap between the data they collect and their ability to use it effectively. This gap stems from several factors:

• The Rise of Probabilistic Marketing: The shift away from deterministic identifiers, especially for mobile, means marketers must increasingly rely on probabilistic models. This requires a higher level of data sophistication and engineering support to accurately calculate KPIs like CTR and predict RPU.
• Privacy and Data Accuracy: More marketing teams are utilizing first party data and sending it directly to the platforms to increase accuracy and privacy controls. Handing this data accurately, and in a secure and privacy-safe manner is crucial.
• Fragmented Data Silos and Integration: Data is often scattered across various platforms, making it difficult to create a unified view of the customer journey. Integrating data from multiple sources, including first-party data, agency data, and various marketing channels, requires significant technical expertise. This fragmentation makes it difficult to get a clear picture of CPM across campaigns and channels.
• The Data Engineering (DE) Bottleneck: Many marketing teams lack dedicated data engineering resources. Even when DEs are available, they may be focused on other priorities, leaving performance marketers struggling to get their data needs met. This can lead to delays in accessing critical data for calculating RPU and other metrics.

The Consequences of Data Inefficiency

This data gap can significantly hinder a performance marketing team’s ability to succeed:

• Missed Opportunities: Without timely and accurate data, marketers may struggle to identify high-performing campaigns, optimize targeting, and capitalize on emerging trends. This can negatively impact CTR and ultimately RPU.
• Inaccurate Attribution: A lack of proper data infrastructure and attribution modeling can lead to inaccurate insights, making it difficult to allocate budgets effectively and understand the true ROI of marketing efforts. This can skew your understanding of CPM and its effectiveness.
• Reduced Agility: Manual data processes and inefficient workflows can slow down decision-making, hindering the team’s ability to quickly adapt to changing market conditions. This can hamper the ability to react to fluctuations in RPU and adjust your strategy accordingly.

Bridging the Gap: Empowering Performance Marketers with Data

To thrive in the new era of performance marketing, teams need to prioritize data accessibility and efficiency. Here’s how:

• Embrace Automation: Automate data ingestion, transformation, and delivery to ensure data is always up-to-date and readily available for analysis. This will allow for real-time tracking of CTR, CPM, and RPU.
• Invest in Data Expertise: Seek out data engineering expertise, Whether you can access internal resources or external partnerships, building robust data pipelines can ensure data quality. This will improve the accuracy and reliability of your KPIs.
• Prioritize Data Integration: Develop a strategy for integrating data from all relevant sources to create a holistic view of the customer journey. This will provide a comprehensive understanding of CPM and its impact on RPU.
• Empower Data-Driven Decision Making: Equip performance marketers with the tools and insights they need to make informed decisions based on accurate and timely data. This will enable data-driven optimization of campaigns to maximize RPU and improve CTR.

By addressing these key areas, performance marketing teams can bridge the data gap, unlock valuable insights, and drive better results in an increasingly complex and competitive landscape.